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The present study was performed to quantify a latent variable for body size (BS) from the five linear body measurements, including body length (BL), body height (BH), chest width (CW), chest girth (CG), and tube girth (TG). The study population consisted of N= 5573 Yorkshire pigs, 592 individuals out of them were genotyped using a PorcineSNP80 BeadChip. The body size latent variable was determined using Confirmatory Factor Analysis (CFA). Then, the accuracy of breeding values was obtained using pedigree-based best linear unbiased prediction (PBLUP), genomic best linear unbiased prediction (GBLUP), and single-step genomic best linear unbiased prediction (ssGBLUP) models. The overall fit indices, including standardized root mean square residual (SRMR), root mean square error of approximation (RMSEA), Tucker-Lewis Index (TLI), and comparative fit index (CFI) were obtained for the BS as 0.03, 0.09, 0.93, and 0.96, respectively which imply the adequacy of the considered model for BS construct. The performance of models was measured in a 5-fold cross-validation with 10 repeats to get a more accurate measure of the model's performance. The accuracy of models was compared via the correlation between predicted breeding values (PBV) and estimated breeding values (EBV) metric which was 0.37, 0.30, and 0.28 for PBLUP, ssGBLUP, and GBLUP, respectively. Furthermore, the goodness of fit is measured by the mean square of error (MSE) and Pearson's correlations r(y,) between observed and predicted phenotypes. The lowest MSE and the highest Pearson's correlations were obtained under PBLUP while the highest MSE and the lowest Pearson's correlations were obtained under GBLUP. The obtained results showed the GBLUP method generally provided lower prediction accuracies than PBLUP and ssGBLUP methods, and also ssGBLUP generated lower prediction accuracy than traditional PBLUP. The performance of ssGBLUP and GBLUP was lower than expected mainly due to the small number of genotyped animals. [ABSTRACT FROM AUTHOR]

Runs of homozygosity (ROH) stretches are continuous homozygous fragments of the genome, which are more suitable for calculating the genomic inbreeding, identifying footprints involved in economic traits and understanding the population history in livestock species. In this study, using a dataset of Ovine SNP50 BeadChip genotypes, the distribution of ROH in nine sheep populations (Soay n= 110, Australian Poll Dorset n=108, Australian Suffolk n=109, Finn sheep n= 99, Scottish Texel n= 80, Scottish Blackface n= 56, Galway n= 49, Border Leicester n= 48, German Texel n=46) from Europe were investigated. ROHs were detected by using PLINK v1.09 with the minimal number of SNPs in ROH set at 40; the maximal gap between the adjacent SNPs was set to 1Mb; the minimum SNP density per ROH was set to 1/100 kb and no heterozygote less than 16 Mb was allowed. The detected ROHs were specified to four categories, based on their length: 1–4 Mb, 4–8 Mb, 8–16 Mb and above 16 Mb. A total of 22,204 ROHs were identified, in which ~ 92 – 98 % were less than 16 Mb in length, covering 4.6% to 12.9% of the entire genome. The inbreeding coefficient based on ROH (FROH) varied among populations (ranging from 0.05 to 0.14). The highest inbreeding rate was found in Border Leicester and Soay breeds. In addition, we detected 90 possible ROH Islands that overlapped with candidate genes associated with different economic traits such as the body weight, meat production, fat deposition, horn-less, and coat color in sheep. Our results suggested that although genetic selection for meat and wool traits in these breeds have been extensively carried out during the last decades, the autozygotic proportion of the genome is still considerably low, and it could lead to an acceptable response to selection in breeding schemes. [ABSTRACT FROM AUTHOR]